研究一类离散和分布时变时滞的混沌神经网络的广义投影同步问题。
In this paper, the problem of general projective synchronization of a class of chaotic neural networks with discrete and distributed time-varying delays is investigated.
对反馈神经网络进行了研究，在分析现有混沌神经网络的工作原理的基础上，提出一种新的混沌神经网络模型。
The study of the feedback neural network, the analysis of the work principle of Hopfield neural network lead to a neural network model with chaotic character .
提出一种关于多层前向神经网络结构的混沌优化设计方法。
The optimization design method is proposed for feed-forward neural network structure by means of chaos ergodicity and randomicity.
基于混沌神经网络的供配电系统故障诊断，采用引入动量项和混沌映射的改进BP算法。
The improved BP algorithm added momentum item and chaotic mapping was adopted in fault diagnosis of power supply system based on chaotic neural network.
考虑神经网络在训练大规模样品时易陷入局部极小，用梯度下降法与混沌优化方法相结合，使神经网络实现快速训练的同时，避免陷入局部极小。
Combining grading method with chaotic optimization, the neural network model achieves rapid training and avoids local minimum when there are a lot of samples to be trained.
提出了一种基于混沌变量的多层模糊神经网络优化算法设计。
An optimization algorithm design based on chaotic variable is proposed for multilayer fuzzy neural network.
本文给出了一种利用线性输出神经网络实现标量混沌信号同步控制的方法。
An approach to the control and synchronization of the scalar chaotic signal by means of neural networks with linear outputs is presented.
根据逆最优控制方法，针对非线性系统，提出了利用动态神经网络产生混沌的一种新方法。
Propose a new approach to generate chaos via dynamic neural networks according to inverse optimal control for nonlinear systems.
最后阐述应用rbf神经网络进行基于混沌的语音信号非线性处理。
Then RBF neural network used in nonlinear processing of speech signals based on chaos aspects is presented.
第三部分对基于混沌优化算法的模糊优选神经网络预测模型进行研究。
In the third part, the prediction model of fuzzy optimal selection neural network based on chaotic optimization algorithm is studied.
采用混沌优化策略，提出一种前馈神经网络权参数的最优学习方案。
In this paper, the optimization design for feed-forward neural network is proposed based on chaos optimization.
为解决压电陶瓷迟滞建模问题，提出一种新型的G - S混沌神经网络模型。
A novel G-S chaotic neural network is proposed to resolve the hysteresis model of piezoceramics.
本文主要研究混沌模拟退火神经网络(CSAN)在求解tsp中的应用。
In this paper, We mainly do researches on using chaotic neural network based on simulated annealing (CSAN) to solve TSP.
具有瞬态混沌特性的神经网络(TCNN)可以解tsp。
Neural Network with Transient Chaos (TCNN) can be used to solve the Traveling Salesman Problem (TSP).
基于混沌变量，提出一种神经网络自适应控制系统的优化设计方案。
In this paper, the optimization design for self-adaptive control system of feed-forward neural network is proposed based on chaotic variable.
提出了一种将混沌的相空间重构、小波包分析和神经网络相结合的新方法用于预测气-固循环流化床的颗粒浓度。
A new hybrid method for prediction of solids holdup in gas-solid circulating fluidized bed is proposed based on chaos phase reconstruction and wavelet package as well as neural networks.
这种用改进了的自组织方法所构成的GMDH型神经网络可以应用于混沌时间序列预测。
An improved GMDH-type neural network and its application to predicting chaotic time series are proposed.
根据混沌系统产生的二进制序列，设定神经网络的权值和阈值，对每一个像素进行加密和解密运算。
According to a binary sequence generated from a chaotic system, the weights and biases of the network are set for the encryption and or decryption of each signal element.
该算法的优点之一是神经网络（NN）隐式混沌映射关系使直接获取映射关系变得困难。
One advantage of the algorithm is that the hidden-mapping model of NN makes it difficult to get the direct mapping function of the ordinary chaos encryption algorithm.
以船舶发电机这一大型非线性系统为例，对其进行混沌神经网络仿真建模研究，提出了用混沌神经网络仿真建模的一般思路和方法。
A general idea and a basic method for modeling with neural networks are put forward on the basis of the study of Marine synchronous generator modeling based on chaotic neural networks.
对于一个经诊断为混沌的统计量序列，应用神经网络建立模型，短期预测混沌序列。
Short term predictions of chaotic series are realised with neural network model, after diagnosing the time series as chaotic statistic series.
分析了BP神经网络和混沌优化的特点，并将混沌优化方法和梯度下降法结合起来构成一种新的组合搜索优化方法。
The characteristics of BP neural network and chaos optimal method are analyzed. By integrating chaos optimal method with gradient-decline method, an optimal method of combination search is created.
已有的研究结果表明，混沌神经网络在求解复杂优化问题和联想记忆等方面比现有网络有着更好的性能。
The research results show that the chaotic neural networks are more effective than other existing neural networks to solve associative memory and complex optimization problems.
回顾了近年来几种主要混沌神经元模型及混沌神经网络的研究进展，介绍了其特点及主要的应用。
Reviews the research progress of chaotic neuron model and chaotic neural networks in recent years, introduces the characteristics and application of the chaotic neural networks.
其次，实验中测得了大量的混沌数据，在神经网络模型的启发下提出了一种新的符号序列去噪算法，应用该算法提高了测量精度。
Secondly, we have obtained plenty of chaotic data, and presented a new method derived from Neural Network theory to process the symbolic series, which improves the accuracy of measurement.
在传统混沌神经网络模型的基础上，提出了一种具有衰减混沌噪声的混沌模拟退火神经网络模型(CSA - DCN)。
Based on deeply discussing the principle of chaotic neural network model, the chaotic simulated annealing model with decaying chaotic noise (CSA-DCN) is presented.
本文研究一类离散神经网络中的混沌及控制混沌问题。
In this paper the chaos and controlling chaos in a class of discrete neural networks are studied.
本文研究一类离散神经网络中的混沌及控制混沌问题。
In this paper the chaos and controlling chaos in a class of discrete neural networks are studied.
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